DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows.
Model details →DeepSeek: DeepSeek V4 Flash 0731 vs Z.ai: GLM 5.2
DeepSeek: DeepSeek V4 Flash 0731 wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering,...
Model details →Side-by-side comparison
| Capability | DeepSeek: DeepSeek V4 Flash 0731 | Z.ai: GLM 5.2 | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 1.0M | 1.0M | Tie |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.09 | $0.10 | 🏆 DeepSeek: DeepSeek V4 Flash 0731 |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.18 | $0.31 | 🏆 DeepSeek: DeepSeek V4 Flash 0731 |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | Yes | Yes | Tie |
Frequently asked questions
Is DeepSeek: DeepSeek V4 Flash 0731 better than Z.ai: GLM 5.2?
DeepSeek: DeepSeek V4 Flash 0731 wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between DeepSeek: DeepSeek V4 Flash 0731 and Z.ai: GLM 5.2?
Input: $0.09 vs $0.10 per 1M tokens. Output: $0.18 vs $0.31 per 1M tokens.
What context windows do DeepSeek: DeepSeek V4 Flash 0731 and Z.ai: GLM 5.2 support?
DeepSeek: DeepSeek V4 Flash 0731 supports up to 1.0M tokens. Z.ai: GLM 5.2 supports up to 1.0M tokens.
Do both DeepSeek: DeepSeek V4 Flash 0731 and Z.ai: GLM 5.2 support tool calling?
DeepSeek: DeepSeek V4 Flash 0731: yes. Z.ai: GLM 5.2: yes.
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